Search results for: ring deep beam

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd

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This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.

Keywords: optimization, reinforced concrete, optimization methods, impact load, earthquake

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Authors: G. Vinitha, A. Ramalingam

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In view of a possible application in optical data storage devices, diffraction grating efficiency of an organic dye, Acid Fuchsin doped in PMMA matrix was studied under excitation with CW diode pumped Nd: YAG laser at 532 nm. The open aperture Z-scan of dye doped polymer displayed saturable absorption and the closed aperture Z-scan of the samples exhibited negative nonlinearity. The diffraction efficiency of the grating is the ratio of the intensity of the first order diffracted power to the incident read beam power. The dye doped polymer films were found to be good media for recording. It is observed that the formation of gratings strongly depend on the concentration of dye in the polymer film, the intensity ratios of the writing beams and the angle between the writing beams. It has been found that efficient writing can be made at an angle of 20° and when the intensity ratio of the writing beams is unity.

Keywords: diffraction efficiency, nonlinear optical material, saturable absorption, surface-relief-gratings

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: Youssef Abdelli, Rachid Nasri

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The large amplitude free vibration analysis of three-layered symmetric sandwich beams is carried out using two different approaches. The governing nonlinear partial differential equations of motion in free natural vibration are derived using Hamilton's principle. The formulation leads to two nonlinear partial differential equations that are coupled both in axial and binding deformations. In the first approach, the method of multiple scales is applied directly to the governing equation that is a nonlinear partial differential equation. In the second approach, we discretize the governing equation by using Galerkin's procedure and then apply the shooting method to the obtained ordinary differential equations. In order to check the validity of the solutions obtained by the two approaches, they are compared with the solutions obtained by two approaches; they are compared with the solutions obtained numerically by the finite difference method.

Keywords: finite difference method, large amplitude vibration, multiple scales, nonlinear vibration

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Authors: H. A. Alguhi, W. A. Elsaigh

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This paper provides a tensile stress-strain (σ-ε) relationship for High-Strength Steel Fiber Reinforced Concrete (HSFRC). Load-deflection (P-δ) behavior of HSFRC beams tested under four-point flexural load were used with inverse analysis to calculate the tensile σ-ε relationship for various tested concrete grades (70 and 90MPa) containing 60 kg/m3 (0.76 %) of hook-end steel fibers. A first estimate of the tensile (σ-ε) relationship is obtained using RILEM TC 162-TDF and other methods available in literature, frequently used for determining tensile σ-ε relationship of Normal-Strength Concrete (NSC) Non-Linear Finite Element Analysis (NLFEA) package ABAQUS® is used to model the beam’s P-δ behavior. The results have shown that an element-size dependent tensile σ-ε relationship for HSFRC can be successfully generated and adopted for further analyzes involving HSFRC structures.

Keywords: tensile stress-strain, flexural response, high strength concrete, steel fibers, non-linear finite element analysis

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Authors: Ewelina Nowak, Anna Wisla-Swider, Gohar Khachatryan, Krzysztof Danel

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Complexes of ionic liquids with different heterocyclic-rings were synthesized by ion exchange reactions with pure salmon DNA. Ionic liquids (ILs) like 1-hexyl-3-methylimidazolium chloride, 1-butyl-4-methylpyridinium chloride and 1-ethyl-1-methylpyrrolidinium bromide were used. The ILs were built into helical state and confirmed by IR spectrometric techniques. Patterns of UV-Vis, photoluminescence, IR, and CD spectra indicated inclusion of small molecules into DNA structure. Molecular weight and radii of gyrations values of ILs-DNA complexes chains were established by HPSEC–MALLS–RI method. Modification DNA with 1-ethyl-1-methylpyrrolidinium bromide gives more uniform material and leads to elimination of high molecular weight chains. Thus, the incorporation DNA double helical structure with both 1-hexyl-3-methylimidazolium chloride and 1-butyl-4-methylpyridinium chloride exhibited higher molecular weight values. Scanning electron microscopy images indicate formation of nanofibre structures in all DNA complexes. Fluorescence depends strongly on the environment in which the chromophores are inserted and simultaneously on the molecular interactions with the biopolymer matrix. The most intensive emission was observed for DNA-imidazole ring complex. Decrease in intensity UV-Vis peak absorption is a consequence of a reduction in the spatial order of polynucleotide strands and provides different π–π stacking structure. Changes in optical properties confirmed by spectroscopy methods make DNA-ILs complexes potential biosensor applications.

Keywords: biopolymers, biosensors, cationic surfactant, DNA, DNA-gels

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

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Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: rotating shaft, flexible blades, centrifugal stiffness, stability

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Authors: Isahakyan Heghine

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Intertextuality, being in the centre of attention of both linguists and literary critics, is vividly expressed in the outstanding British novelist and philosopher J. Fowles' works. 'The Magus’ is a deep psychological and philosophical novel with vivid intertextual links with the Greek mythology and authors from different epochs. The aim of the paper is to show how intertextuality might serve as a dialogue between two authors (J. Fowles and J. Donne) disguised in the dialogue of two protagonists of the novel : Conchis and Nicholas. Contrastive viewpoints concerning man's isolation, loneliness are stated in the dialogue. Due to the conceptual analysis of the text it becomes possible both to decode the conceptual information of the text and find out its intertextual links.

Keywords: dialogue, conceptual analysis, isolation, intertextuality

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Authors: Jolene M. Helena, Annie M. Joubert, Peace Mabeta, Magdalena Coetzee, Roy Lakier, Anne E. Mercier

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Targeting the distant tumour and its microenvironment whilst preserving bone density is important in improving the outcomes of patients with bone metastases. 2-Ethyl-3-O-sulphamoyl-estra1,3,5(10)16-tetraene (ESE-16) is an in-silico-designed 2- methoxyestradiol analogue which aimed at enhancing the parent compound’s cytotoxicity and providing a more favourable pharmacokinetic profile. In this study, the potential radiosensitization effects of ESE-16 were investigated in an in vitro bone metastasis model consisting of murine pre-osteoblastic (MC3T3-E1) and pre-osteoclastic (RAW 264.7) bone cells, metastatic prostate (DU 145) and breast (MDA-MB-231) cancer cells, as well as human umbilical vein endothelial cells (HUVECs). Cytotoxicity studies were conducted on all cell lines via spectrophotometric quantification of 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide. The experimental set-up consisted of flow cytometric analysis of cell cycle progression and apoptosis detection (Annexin V-fluorescein isothiocyanate) to determine the lowest ESE-16 and radiation doses to induce apoptosis and significantly reduce cell viability. Subsequent experiments entailed a 24-hour low-dose ESE-16-exposure followed by a single dose of radiation. Termination proceeded 2, 24 or 48 hours thereafter. The effect of the combination treatment was investigated on osteoclasts via tartrate-resistant acid phosphatase (TRAP) activity- and actin ring formation assays. Tumour cell experiments included investigation of mitotic indices via haematoxylin and eosin staining; pro-apoptotic signalling via spectrophotometric quantification of caspase 3; deoxyribonucleic acid (DNA) damage via micronuclei analysis and histone H2A.X phosphorylation (γ-H2A.X); and Western blot analyses of bone morphogenetic protein-7 and matrix metalloproteinase-9. HUVEC experiments included flow cytometric quantification of cell cycle progression and free radical production; fluorescent examination of cytoskeletal morphology; invasion and migration studies on an xCELLigence platform; and Western blot analyses of hypoxia-inducible factor 1-alpha and vascular endothelial growth factor receptor 1 and 2. Tumour cells yielded half-maximal growth inhibitory concentration (GI50) values in the nanomolar range. ESE-16 concentrations of 235 nM (DU 145) and 176 nM (MDA-MB-231) and a radiation dose of 4 Gy were found to be significant in cell cycle and apoptosis experiments. Bone and endothelial cells were exposed to the same doses as DU 145 cells. Cytotoxicity studies on bone cells reported that RAW 264.7 cells were more sensitive to the combination treatment than MC3T3-E1 cells. Mature osteoclasts were more sensitive than pre-osteoclasts with respect to TRAP activity. However, actin ring morphology was retained. The mitotic arrest was evident in tumour and endothelial cells in the mitotic index and cell cycle experiments. Increased caspase 3 activity and superoxide production indicated pro-apoptotic signalling in tumour and endothelial cells. Increased micronuclei numbers and γ-H2A.X foci indicated increased DNA damage in tumour cells. Compromised actin and tubulin morphologies and decreased invasion and migration were observed in endothelial cells. Western blot analyses revealed reduced metastatic and angiogenic signalling. ESE-16-induced radiosensitization inhibits metastatic signalling and tumour cell survival whilst preferentially preserving bone cells. This low-dose combination treatment strategy may promote the quality of life of patients with metastatic bone disease. Future studies will include 3-dimensional in-vitro and murine in-vivo models.

Keywords: angiogenesis, apoptosis, bone metastasis, cancer, cell migration, cytoskeleton, DNA damage, ESE-16, radiosensitization.

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

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An acoustic micro-energy harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using lumped element modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Hence, AMEH mathematical model is validated. Then, AMEH undergoes bandwidth tuning for performance optimization for further experimental work. The AMEH successfully produces 0.9 V⁄(m⁄s^2) and 1.79 μW⁄(m^2⁄s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. By integrating a capacitive load of 200µF, the discharge cycle time of AMEH is 1.8s and the usable energy bandwidth is available as low as 0.25g. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: piezoelectric, acoustic, energy harvester

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Authors: Rakesh Dogra, Arun Kumar, Arvind Kumar Sharma

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This paper reports the thermoluminescence as well as optical properties of rare earth doped lithium fluoride (LiF) nanophosphor, synthesized via chemical route. The rare earth impurities (Yb and Sm) have been observed to increase the deep trap center capacity, which, in turn, enhance the radiation resistance of the LiF. This suggests the viability of these materials to be used as high dose thermoluminescent detectors at high temperature. Further, optical absorption measurements revealed the formation of radiation induced stable color centers in LiF at room temperature, which are independent of the rare earth dopant.

Keywords: lithium flouride, thermoluminescence, UV-VIS spectroscopy, Gamma radiations

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Authors: Abdoullah Namdar, Fadzil Mat Yahaya

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Many synthetic additives have been using for improve cement mortar and concrete characteristics, but natural additive is a friendly environment option. The quantity of (2% and 4%) seashell powder has been replaced in cement mortar, and compared with plain cement mortar in early age of 7 days. The strain gauges have been installed on beams and cube, for monitoring fluctuation of flexural and compressive strength. Main objective of this paper is to study effect of linear static force on flexural and compressive strength of modified cement mortar. The results have been indicated that the replacement of appropriate proportion of seashell powder enhances cement mortar mechanical properties. The replacement of 2% seashell causes improvement of deflection, time to failure and maximum load to failure on concrete beam and cube, the same occurs for compressive modulus elasticity. Increase replacement of seashell to 4% reduces all flexural strength, compressive strength and strain of cement mortar.

Keywords: compressive strength, flexural strength, compressive modulus elasticity, time to failure, deflection

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Authors: Qianwei Cheng, A. K. M. Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem, Ovi Paul, Amin Ahsan Ali, M. Ashraful Amin, Ryosuke Shibasaki, Moinul Zaber

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Thomas Friedman, in his famous book, argued that the world in this 21st century is flat and will continue to be flatter. This is attributed to rapid globalization and the interdependence of humanity that engendered tremendous in-flow of human migration towards the urban spaces. In order to keep the urban environment sustainable, policy makers need to plan based on extensive analysis of the urban environment. With the advent of high definition satellite images, high resolution data, computational methods such as deep neural network analysis, and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding urban space lies in useful categorization of the space that is usable for data collection, analysis, and visualization. In this paper, we propose a pragmatic categorization method that is readily usable for machine analysis and show applicability of the methodology on a developing world setting. Categorization to plan sustainable urban spaces should encompass the buildings and their surroundings. However, the state-of-the-art is mostly dominated by classification of building structures, building types, etc. and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh, where the surrounding environment is crucial for the categorization. Moreover, these categorizations propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real time. Our proposed method is divided into two steps-categorization and automation. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently a map was drawn. The categorization is based broadly on two dimensions-the state of urbanization and the architectural form of urban environment. Consequently, the urban space is divided into four categories: 1) highly informal area; 2) moderately informal area; 3) moderately formal area; and 4) highly formal area. In total, sixteen sub-categories were identified. For semantic segmentation and automatic categorization, Google’s DeeplabV3+ model was used. The model uses Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate larger context. Image encompassing 70% of the urban space was used to train the model, and the remaining 30% was used for testing and validation. The model is able to segment with 75% accuracy and 60% Mean Intersection over Union (mIoU). In this paper, we propose a pragmatic categorization method that is readily applicable for automatic use in both developing and developed world context. The method can be augmented for real-time socio-economic comparative analysis among cities. It can be an essential tool for the policy makers to plan future sustainable urban spaces.

Keywords: semantic segmentation, urban environment, deep learning, urban building, classification

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Authors: Sourabh R. Dinde, Rajshekar S. Talikoti

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According to the structural point of view Industrial Pallet rack structure can be considered typical steel framed structure. This work presents a general analysis of an industrial pallet rack structure, evaluating the influence of each of the components on the global stability. An analytical study for the sensitivity of pallet rack configuration in linear static equivalent lateral loads. The aim is to braced/unbraced frames were design and their analytical models are to be built in software. The finite element analysis is used to determine axial forces in beam and column, maximum storey displacement and buckling loads on braced/unbraced pallet rack structure. Bracing systems are mostly provided to enhance the stiffness factor of the structures with the seismic loads. Unbraced systems have mostly translational modes of failure and are very flexible due to excessive loads.

Keywords: buckling capacity, cold formed steel, finite element analysis, pallets Rrack, seismic design

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Authors: O. Squillace, R. L. Thompson

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Migration of small molecules to, and across the surface of polymer matrices is a little-studied problem with important industrial applications. Tackifiers in adhesives, flavors in foods and binding agents in paints all present situations where the function of a product depends on the ability of small molecules to migrate through a polymer matrix to achieve the desired properties such as softness, dispersion of fillers, and to deliver an effect that is felt (or tasted) on a surface. It’s been shown that the chemical and molecular structure, surface free energies, phase behavior, close environment and compatibility of the system, influence the migrants’ motion. When differences in behavior, such as occurrence of segregation to the surface or not, are observed it is then of crucial importance to identify and get a better understanding of the driving forces involved in the process of molecular migration. In this aim, experience is meant to be allied with theory in order to deliver a validated theoretical and computational toolkit to describe and predict these phenomena. The systems that have been chosen for this study aim to address the effect of polarity mismatch between the migrants and the polymer matrix and that of a second migrant over the first one. As a non-polar resin polymer, polyvinyl acetate is used as the material to which more or less polar migrants (sorbitol, carvone, octanoic acid (OA), triacetin) are to be added. Through contact angle measurement a surface excess is seen for sorbitol (polar) mixed with PVAc as the surface energy is lowered compare to the one of pure PVAc. This effect is increased upon the addition of carvon or triacetin (non-polars). Surface micro-structures are also evidenced by atomic force microscopy (AFM). Ion beam analysis (Nuclear Reaction Analysis), supplemented by neutron reflectometry can accurately characterize the self-organization of surfactants, oligomers, aromatic molecules in polymer films in order to relate the macroscopic behavior to the length scales that are amenable to simulation. The nuclear reaction analysis (NRA) data for deuterated OA 20% shows the evidence of a surface excess which is enhanced after annealing. The addition of 10% triacetin, as a second migrant, results in the formation of an underlying layer enriched in triacetin below the surface excess of OA. The results show that molecules in polarity mismatch with the matrix tend to segregate to the surface, and this is favored by the addition of a second migrant of the same polarity than the matrix. As studies have been restricted to materials that are model supported films under static conditions in a first step, it is also wished to address the more challenging conditions of materials under controlled stress or strain. To achieve this, a simple rig and PDMS cell have been designed to stretch the material to a defined strain and to probe these mechanical effects by ion beam analysis and atomic force microscopy. This will make a significant step towards exploring the influence of extensional strain on surface segregation, flavor release in cross-linked rubbers.

Keywords: polymers, surface segregation, thin films, molecular migration

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Authors: M. Akhlaque Ahmed, Maliha Afshan, Adeel Tahir

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Global and diffuse solar radiation studies have been carried out for the Capital city of Pakistan, Islamabad ( latitude 330 43’N and Longitude 370 71’E) to assess the solar potential of the area. The global and diffuse solar radiation were carried out using sunshine hour data for the above-mentioned area. Monthly total solar radiation is calculated through regression constants a and b through declination angle of the sun and sunshine hours and KT that is cloudiness index are used to calculate the diffuse solar radiation. Result obtained shows variation in the direct and diffuse component of solar radiation in summer and winter months for Islamabad. Diffuse solar radiation was found maximum in July, i.e., 32% whereas direct or beam radiation was found to be high in April to June, i.e., 73%. During July, August, and December, the sky was found cloudy. From the result, it appears that with the exception of monsoon month July and August the solar energy can be utilized very efficiently throughout the year in Islamabad.

Keywords: global radiation, Islamabad, diffuse radiation, sky condition, sunshine hour

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Kiran Abdullah, Yanli Chen

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An amphiphilic mixed (phthalocyaninato) (porphyrinato) europium triple-decker complex Eu₂(Pc)₂(TPyP) has been synthesized and characterized. Introducing electron-withdrawing pyridyl substituents onto the meso-position of porphyrin ring in the triple-decker to ensure the sufficient hydrophilicity and suitable HOMO and LUMO energy levels and thus successfully realize amphiphilic ambipolar organic semiconductor. Importantly, high sensitive, reproducible p-type and n-type responses towards NH₃ andNO₂ respectively, based on the self-assembled film of the Eu₂(Pc)₂(TPyP) fabricated by a simple solution-based Quasi–Langmuir–Shäfer (QLS) method, have been first revealed. The good conductivity and crystallinity for the QLS film of Eu₂(Pc)₂(TPyP) render it excellent sensing property. This complex is sensitive to both electron-donating NH₃ gas in 5–30 ppm range and electron-accepting NO₂ gas 400–900 ppb range. Due to uniform nano particles there exist effective intermolecular interaction between triple decker molecules. This is the best result of Phthalocyanine–based chemical sensors at room temperature. Furthermore, the responses of the QLS film are all linearly correlated to both NH₃ and NO₂ with excellent sensitivity of 0.04% ppm⁻¹ and 31.9 % ppm⁻¹, respectively, indicating the great potential of semiconducting tetrapyrrole rare earth triple-decker compounds in the field of chemical sensors.

Keywords: ambipolar semiconductor, gas sensing, mixed (phthalocyaninato) (porphyrinato) rare earth complex, Self-assemblies

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Authors: Mitat Uysal, Aynur Uysal

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Computer engineering and mathematics share a deep and symbiotic relationship, with mathematics providing the foundational theories and models for computer engineering advancements. From algorithm development to optimization techniques, mathematics plays a pivotal role in solving complex computational problems. This paper explores key mathematical principles that underpin computer engineering, illustrating their significance through a case study that demonstrates the application of optimization techniques using Python code. The case study addresses the well-known vehicle routing problem (VRP), an extension of the traveling salesman problem (TSP), and solves it using a genetic algorithm.

Keywords: VRP, TSP, genetic algorithm, computer engineering, optimization

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Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

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Authors: Meihua Fang, Tao Fei

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Post-processing can effectively improve the resistance to laser damage in multilayer films used in a high power laser system. In this work, HfO₂/SiO₂ multilayer films are prepared by e-beam evaporation and then β-ray irradiation is employed as the post-processing method. The particle irradiation affects the laser induced damage threshold (LIDT), which includes defects, surface roughness, packing density, and residual stress. The residual stress that is relaxed during irradiation changes from compressive stress into tensile stress. Our results indicate that appropriate tensile stress can improve LIDT remarkably. In view of the fact that LIDT rises from 8 J/cm² to 12 J/cm², i.e., 50% increase, after the film has been irradiated by 2.2×10¹³/cm² β-ray, the particle irradiation can be used as a controllable and desirable post-processing method to improve the resistance to laser induced damage.

Keywords: β-ray irradiation, multilayer film, residual stress, laser-induced damage threshold

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Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Michel Moliere

Abstract:

In the next decades, the thermal power generation segment will survive only if it achieves deep mutations, including drastical abatements of CO2 emissions and strong efficiency gains. In this challenging perspective, stationary gas turbines appear as serious candidates to lead the energy transition. Indeed, during the past decades, these turbomachines have made brisk technological advances in terms of efficiency, reliability, fuel flex (including the combustion of hydrogen), and the ability to hybridize with regenrables. It is, therefore, timely to summarize the progresses achieved by gas turbines in the recent past and to examine what are their assets to face the challenges of the energy transition.

Keywords: energy transition, gas turbines, decarbonization, power generation

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Authors: Camilla G. Goncalves, Benedito Christ, Walter Miyakawa, Antonio J. Abdalla

Abstract:

This work aims to investigate the properties and microstructure of diamond-like carbon film deposited by pulsed laser deposition by ablation of a graphite target in a vacuum chamber on a steel substrate. The equipment was mounted to provide one laser beam. The target of high purity graphite and the steel substrate were polished. The mechanical and tribological properties of the film were characterized using Raman spectroscopy, nanoindentation test, scratch test, roughness profile, tribometer, optical microscopy and SEM images. It was concluded that the pulsed laser deposition (PLD) technique associated with the low-pressure chamber and a graphite target provides a good fraction of sp3 bonding, that the process variable as surface polishing and laser parameter have great influence in tribological properties and in adherence tests performance. The optical microscopy images are efficient to identify the metallurgical bond.

Keywords: characterization, DLC, mechanical properties, pulsed laser deposition

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

Abstract:

Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Arleta Rifati Nixha, Mustafa Arslan, Adem Ergün, Nahit Gencer

Abstract:

Polyphenol oxidase (PPO), sometimes referred to as phenol oxidase, catecholase, phenolase, catechol oxidase, or even tyrosinase, is considered to be an o-dipenol. PPO (EC 1.14.18.1), a multifunctional copper containing enzyme, is widely distributed in nature. It catalyzes two distinct reactions of melanin synthesis: a hydroxylation of monophenols to o-diphenols (monophenolase activity) and an oxidation of o-diphenols to o-quinones (diphenolase activity), both using molecular oxygen. Additionaly, investigation demonstrated that various dermatological disorders, such as age spots and freckle, were caused by the accumulation of an excessive level of epidermal pigmentation. Tyrosinase has also been linked to Parkinson’s and other neurodegenerative diseases. Nitrogen heterocycles have received a great deal of attention in the literature because of biological properties. Especially, among these heterocyclic systems, pyridine containing compounds have been the subject of expanding research efforts in heteroaromatic and biological chemistry. The pyrido [2,3-d] pyrimidine heterocycles, which are those annelated to a pyrimidine ring, are important because of their wide range of biological and pharmaceutical applications (i.e., bronchodilators, vasodilators) and their anti-allergic, cardiotonic, antihypertensive, and hepatoprotective activities. In this study series of 12 new carbazole substituted pyridopyrimidine urea(thiourea) derivatives were synthesized and evaluated effect on PPO. Additionally, we presented structure-activity relationship analyses and theoretical calculations of the compounds.

Keywords: carbazole, pyridopyrimidine, urea, thiourea, tyrosinase inhibitors

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